With the ever-increasing data traffic demand in today's mobile networks, immediate solutions for capacity improvement are sought by the operators. Thanks to higher spatial reuse of spectrum, short-radius cell in the range of 50 to 100 meters appear as a promising solution to satisfy bandwidth extensive traffic demands and to enhance the Quality of Experience (QoE) of mobile users.
Heterogeneous Networks (HetNet) are now being deployed, where cells of smaller footprint size (so-called pico, metro or micro cells) are embedded within the coverage area of larger umbrella cells (so-called macro cells), primarily to provide increased capacity in targeted areas of data traffic concentration. HetNet try to exploit the spatial variation in user and traffic distribution to efficiently increase the overall capacity of mobile networks.
HetNet poses new challenges for efficient network planning and operation.
So far, network planning and operation are based on expensive drive tests for gathering radio measurements within a given geographical area and identifying possible coverage holes, as well as on intensive network configuration, including adding or moving antenna sites, and optimizing radio transmission parameters (antenna tilt and gain, transmit spectrum, transmit power, etc).
Alternatively, network planning and operation may be based on radio propagation models from known antenna locations. 3D geographical maps are then fed to the radio propagation models, together with further radio transmission parameters, so as to guess what the receive signal and interference level is expected to be at a particular geographical location, and further to determine an optimal network configuration.
These network planning tools are well suited for legacy mobile networks, which mostly accommodate macro cells at known locations. With the ever increasing number of small cells being deployed for next-generation mobile networks, these tools prove inefficient and inaccurate.
Also, the current network configuration gets very quickly outdated as the radio propagation environment always changes owing to new construction works (e.g., new high buildings, old buildings being torn down), or owing to new cells being brought into service or existing cells being brought out of commission (which may alter the observed level of interference at a given location), or still owing to weather or season impacts (e.g., tree leaves, snow falls), yielding sub-optimal network performances.
Another important issue for today mobile networks is sustainable development, which is a long-term commitment for all people in the world. Manufacturer should do their best to handle the resource shortage and environment deterioration by improving the power efficiency of the mobile networks, thereby reducing greenhouse emissions and Operational Expenditures (OPEX). Thus, the power efficiency in the infrastructure and terminal becomes an essential part of the cost-related requirements in mobile networks, and there is a strong push to investigate possible network energy saving solutions.
One of this solution is to switch small idle cells into some kind of sleeping (or dormant) mode during low-activity periods, their traffic being handled by still-active neighboring cells, further referred to as coverage cells.
Switching off cells may however bring about coverage holes and/or QoE degradations, and one needs to come up with a solution to wake up the dormant cells whenever appropriate.
The technical specification entitled “Potential Solutions for Energy Saving for E-UTRAN (Release 10)”, ref. 3GPP TR 36.927 V10.1.0, published by the 3rd Generation Partnership Project (3GPP) in September 2011, describes different methods for switching the dormant cells back into operation.
Cells may enter or leave dormant mode based on centralized Operation And Maintenance (OAM) decisions, which are made based on statistical information, e.g. load information, quality metrics, etc. The OAM decisions can be pre-configured or directly signaled to the cells.
As an alternative solution, when cells are in dormant mode and the load increases on the coverage cell, the coverage cells may not know the most appropriate dormant cells to wake-up. The coverage cells may wake-up one or more of the neighboring dormant cells. The final decision to leave dormant mode is however taken by the dormant cell based on information locally available.
As a third solution, when the coverage cell detects high load, it uses a proprietary algorithm to decide which dormant cells should be activated. The algorithm could rely on pre-defined ‘low-load periods’ policies for each neighbor cell. The ‘low-load periods’ information can first be derived from OAM based performance counters, and then the decision implemented in the coverage cell.
As a fourth solution, when the coverage cell detects high load, it can request some dormant cells to switch on their listening capability to perform and report Interference over Thermal (IoT) measurements as defined in 3GPP TS 36.214.
As a fifth solution, when the coverage cell detects high load, it can request some dormant cells to transmit the pilot signal for at least a short time interval (the so-called ‘probing’ interval). After this interval, all or some these cells will return to dormant mode. The User Equipment (UE) covered by the coverage cell will be configured to perform radio measurements for those cells during this interval and to send back measurement results. Based on the measurement results, the coverage cell will then determine which cells should be switched on.
As a sixth solution, when the coverage cell detects high load, it can use a combination of UEs locations, cell locations, and cell radii/transmit powers in deciding which dormant cells should be switched on. Furthermore, a timer value can be included in the activation request message sent from the coverage cell to the selected dormant cells. Upon timer expiry, the cell verifies if the condition required for staying on has been met, and else, goes back to dormant mode.